Essays on Banking and Capital: An Agent-Based Investigation

Abstract:

How do institutional arrangements in banking affect the occurrence of crises?
The first two chapters present an endeavor in using new modeling techniques to
answer this question. Even if the results are not widely accepted, the way in
which the problem is tackled here is offered for consideration and debate. Is
capital the result of an evolving process that takes advantages of entrepreneurial
networks? The last chapter put forth a model wherein firms develop economic
ties with one another. By doing so, a market network unfolds along time as an
spontaneous process.
In the first chapter, I explore the occurrence of bank runs by developing a
sensitivity analysis to the model in Diamond and Dybvig (1983). I implement an
agent-based economic model to analyze different modifications and extensions
to the original. In 36 experiments based on three different versions of the one-bank
model the frequency of bank runs dropped from 42% to 17%. This was due
to changes in the payoffs structure and social network effects whereby depositors
go to the bank if at least three of their proximate neighbors went previously.
What is the role of interbank markets and central banks in coping with banking
crises? In experiments using an agent-based framework with multiple banks and
an interbank market. I found that when banks cannot interact, then runs in
isolated banks occur with a higher frequency than when banks have equal
market shares. That is, there are no runs escalating to systemic panics. In
contrast, if one bank has a market share twice as big as the rest, runs spread.
The presence of a central bank may unexpectedly increase the occurrence of
bank runs. Institutional complexity helps to reduce the frequency of bank runs.
Hence, decentralized institutional structures perform better than centralized ones.
The objective in this chapter is to implement a parsimonious agent-based
computational model of economic networks whereby agents make strategic
decisions based upon profits and information generated through their immediate
social network. In this model firms are represented by nodes and the links
between each pair of them are the result of a mutually advantageous economic
decision. Therefore, links are two-sided or undirected. The economic decision is
based on two elements, namely: a myopic profit motive and local information
channeled through collaborating firms. Here I endogenize the formation and
deletion of links. Furthermore the number of firms (nodes) in the network at each
time by allowing firms (nodes) to enter and exit the market. Centrality measures
are reported together with firms’ profits. The evolution of the network yields
higher connectivity and profits when the (positive) externality is high and the rule
to exit the market more strict. The higher the network connectivity, the higher the
overall profits of firms.